Capacidade produtiva e sua variação espacial de plantios clonais de Tectona grandis linn F. em Capitão Poço, Estado do Pará, Brasil.

Abstract

This work aimed at evaluating the productive capacity and its spatial variability of Tectona grandis Linn F. clonal plantations in Capitão Poço, State of Pará, Brazil, belonging to the company Tietê Agrícola LTDA. Plantation development was monitored by means of continuous forest inventory, using the fixed area method, with 43 circular permanent sample plots systematically arranged in a 320 m x 320 m grid . The following variables were measured: Total height (Ht), diameter at breast height (DBH); age and geographical coordinates at the center of each plot were also registered. Dominant heights (Hd), were determined according toAssmann´s definition. Determination of the site index curves was carried out by regression method, applying anamorphic curves. Three classes of productive capacity were considered: low (III), medium (II) and high (I) productivity classes. An analysis of the spatial variability of the Site Index was performed using geostatistics processes, which consisted of a variographic analysis and kriging interpolation. To estimate the Dominant Height, three semivariograms models were applied viz. Spherical, Gaussian and Exponential. Results of the site index classification revealed three different productivity classes, generating curves with SI 15.5 (Class III), SI 17.5 (Class II) and SI 19.5 m (Class I) for the stand planted in 2010 and curves with SI 12.3 (Class III), SI 14.8 (Class II) and SI 17.3 m (Class I) for stands planted in 2012 and 2013. Dominant height was better estimated by the exponential semivariogram model, generating an interpolated grid of points that allowed visualizing the behavior of the dominant height from the ordinary kriging. A map of site index was then produced where 69.2% (253ha) of the area (365.38 ha) was classified as of average productivity (class II) and 30.8% (112.6 ha) classified as high productivity (class I). Site index is commonly used as a tool to planning establishment of tree plantation crops. In this context, kriging proved to be very efficient because allowed defining site indices for areas not sampled. Therefore in areas with different productive potentials (SI) proper management alternatives can be applied to optimize production.